AI Engineering
Hire an AI engineer for LLM products & agents
I ship production LLM systems — agents with MCP, end-to-end AI products, and paid acquisition with tracking that recovers ROAS. Barcelona-based, remote-friendly, founder-mode when you need it.
Offer
What I take on.
01
AI agents & MCP
Production agents that call real tools — WhatsApp, CRMs, calendars, internal APIs — via Model Context Protocol and LLM tool use. Multi-tenant where it matters, BYOK when cost control matters more.
02
LLM products end-to-end
From brief to shipped SaaS: Next.js, TypeScript, Supabase, auth, billing hooks, and model pipelines that survive contact with real users — not demos that die in a notebook.
03
Paid acquisition + tracking
Google and Meta campaigns with measurement that still works post-iOS14: GA4, GTM, server-side tracking, and dashboards so spend maps to outcomes instead of vibes.
Proof
Shipped, not hypothetical.
LiveClaient: AI WhatsApp client agent with Claude
AI WhatsApp client agent: answers & qualifies leads 24/7 with Claude. Multi-tenant, BYOK.
Read case study →
LiveAdorea.ai: shipping an AI marketing product end-to-end
Shipping an AI marketing SaaS end-to-end: SEO, imagery, calendars, WP & Shopify.
Read case study →
ShippedDTC paid acquisition with tracking that recovers ROAS
DTC paid acquisition on Google + Meta: server-side tracking, creative tests, scaled ROAS.
Read case study →
LiveDairector: AI film production with Claude Script Doctor
AI film production platform: Claude Script Doctor, dramatic-arc analysis, script to post.
Read case study →
How I work
Stack & timeline.
Default stack
- TypeScript
- Next.js
- React
- Node.js
- Python
- Supabase
- Claude / Anthropic
- OpenAI
- MCP
- WhatsApp Cloud API
- GA4 / GTM
- Google Ads
- Meta Ads
Flexible when the client stack requires it (PHP, WordPress, existing backends). The constant is shipping something users can touch.
Week 0–1
Scope & stack
Clarify the outcome, constraints, and success metrics. Pick the smallest stack that can ship — usually TypeScript / Next.js plus the model and tools you already trust.
Week 1–3
Build the spine
Core flows first: auth, data model, the agent or LLM path, and one happy-path integration. You get something clickable early, not a wall of slides.
Week 3–5
Harden & instrument
Edge cases, observability, cost controls, and tracking. If growth is in scope, wire campaigns and attribution before scaling spend.
Ongoing
Ship & iterate
Launch, watch real usage, then tighten prompts, tools, and funnels. I stay close through the first production weeks so nothing drifts.
FAQ
Quick answers.
- Who is a good fit to hire you as an AI engineer?
- Founders and teams that need an LLM product or agent shipped end-to-end — not just a prototype. Ideal when product, engineering, and (optionally) paid acquisition need to move together.
- Do you build MCP and production AI agents?
- Yes. Agents with tool use, WhatsApp and API integrations, multi-tenant setups, and Model Context Protocol where it fits. The bar is production use, not a weekend demo.
- What does a typical engagement look like?
- A clear outcome, a short discovery week, then build in 3–5 week slices with something usable early. Stack defaults to TypeScript, Next.js, and Claude or OpenAI unless your system requires otherwise.
- Are you available remotely from Barcelona?
- Yes. Based in Barcelona and hybrid/remote-friendly. Collaboration works over email, LinkedIn, and the usual async tools.
Get in touch
Let’s ship the agent — or the product.
Tell me what you want live in the next few weeks. AI engineering, full-stack LLM products, paid acquisition rebuilds — if it’s interesting to build, I’m in.